Abstract
This paper describes the transformer-based Neural Machine translation (NMT) system for the Low-Resource Indic Language Translation task for the English-Manipuri language pair submitted by the Centre for Natural Language Processing in National Institute of Technology Silchar, India (NITS-CNLP) in the WMT 2023 shared task. The model attained an overall BLEU score of 22.75 and 26.92 for the English to Manipuri and Manipuri to English translations respectively. Experimental results for English to Manipuri and Manipuri to English models for character level n-gram F-score (chrF) of 48.35 and 48.64, RIBES of 0.61 and 0.65, TER of 70.02 and 67.62, as well as COMET of 0.70 and 0.66 respectively are reported.
Cite
CITATION STYLE
Singh, K. B., Singh, N. A., Meetei, L. S., Bandyopadhyay, S., & Singh, T. D. (2023). NITS-CNLP Low-Resource Neural Machine Translation Systems of English-Manipuri Language Pair. In Conference on Machine Translation - Proceedings (pp. 965–969). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.wmt-1.92
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